MEIS 2015 : A Multilayered Model for Artificial Intelligence of Game Character as Agent Architecture

A Multilayered Model for

Artificial Intelligence of Game Character

as Agent Architecture*

Youichiro Miyake @miyayou https://www.facebook.com/youichiro.miyake

[email protected]

2016.9.26 (Sat)

@Nishijin Plaza Kyushu University

http://mcg.imi.kyushu-u.ac.jp/meis2015/

https://www.facebook.com/youichiro.miyake

https://www.facebook.com/youichiro.miyake

mailto:[email protected]





Summary

• I am a game developer in game industry for more than 10 years.

• My research is focused on AI in digital game.

• There are some mathematical structures in AI.

• I want to show it in talk…

Contents

1. Introduction

2. Agent Architecture

3. Blackboard Architecture

4. Agent Architecture with Blackboard architecture

5. Subsumption Architecture

6. MODERN AGENT Architecture for A game Character

7. Umwelt

8. Hierarchical structure / commutative diagram / Homomorphism in Agent Architecture

9. Summary

INTRODUCTION

Introduction

• From classical AI to modern AI.

• It means from scripted AI to autonomous AI.

Level

Navigation AI

Meta-AI

Character AI

Dynamic allocation of enemies Observing level in real-time Direction for agents Making progress of game

Autonomous thinking Cooperation Team AI

Preparing data to make meta-AI and character AI recognize the level Managing object representation Managing Navigation data Path-finding / Tactical point analysis

Support

Enemy character

Player

Information Acquisition

Control

Brain

http://dear-croa.d.dooo.jp/download/illust.html

http://www.kaiyodo.co.jp/revoltech/yamaguchi_2012.html

Contents

1. Introduction






7. Umwelt


9. Summary

AGENT ARCHITECTURE

Technological Innovation

Time

Scale

The Industrial Revolution

Information Revolution

Network Revolution

Intelligence Revolution

Automation

Computerization

Networked

Intelligent

The 2nd Industrial Revolution

Motorization

1750 1860 1960 1990 Now…

Into “Intelligent” Wolrd

Society and AI

Robot

Generation

Poppulation

AI

ageing society with fewer children Robot and AI will support ageing society with fewer children

© 2015 SQUARE ENIX CO., LTD. All rights reserved

Intelligent Game System

Game System Intelligent

Game System

Digital Games also has become intelligent. So, what is “Intelligent Game System” ?

What is digital game ?

• Interactive Digital Space

• The space becomes structured.

• AI becomes a module

The System of digital game AI

• A role of AI in digital game become clear.

• There are three roles of AI.

AI to control a whole game system

AI of character (Character’s Brain)

AI to recognize an environment in game by analyzing a level, terrain, and space.

Meta AI

Character AI

Navigation AI

Two Axis to categorize AI • The problem of “What is AI” is very difficult problem. • We had better know what problem AI is seeking to resolve.

Space Scale

Time Scale

Local Short time

Global timeless

Global Long time

Meta-AI

Character AI

Navigation AI

Level

Navigation AI

Meta-AI

Character AI

Dynamic allocation of enemies Observing level in real-time Direction for agents Making progress of game

Autonomous thinking Cooperation Team AI

Preparing data to make meta-AI and character AI recognize the level Managing object representation Managing Navigation data Path-finding / Tactical point analysis

Support

Enemy character

Player

Brain

Information Acquisition

Control

http://dear-croa.d.dooo.jp/download/illust.html


Environment and Character

Environment

Character

Character has interactions with an environment.



Environment

Character


IN PUT



Environment

Character


IN PUT

OUT PUT



Environment

Character Intelligence


IN PUT

OUT PUT


Intelligence

World

Sensor

Information Flow

Effector

Agent Architecture

Game World

（Environment/Level）

Five senses

Body

Language

Knowledge Representation

Knowledge Making

Decision Making

Body

Motion Making

Information Flow

Memory Internal Cyclic Information Flow

Sensor

Effector

Intelligence

Agent Architecture

Information Flow

• Information flow connects the outer (environment) and the inner(=intelligence).

• This is caused by mental activity to organize the inner mind’s dynamics.

Information Flow

Internal Cyclic Information Flow

Making AI is achieved by designing Information flow. In actually, there are many information flow inside a mind.

Contents

1. Introduction






7. Umwelt


9. Summary

BLACKBOARD ARCHITECTURE

Blackboard

KS

KS

KS

KS

KS

KS

Arbiter

Bruce Blumberg , Damian Isla, "Blackboard Architectures", AI Game Programming Wisdom (Charles River Media) , 2002

Blackboard Architecture (Knowledge-based AI)

Each KS (Knowledge Source) has special knowledge for a problem. KS read and write information on Blackboard. Arbiter controls all of KS.

All KSs communicate with each other via Blackboard.

Hierarchical Blackboard

Primitive data

Analyzed data

More analyzed data

More analyzed data

More analyzed data

KS

KS

KS

KS

Erman et Al. The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty, ACM Computing Surveys (CSUR) Surveys Homepage archive Volume 12 Issue 2, June 1980, Pages 213-253 http://dl.acm.org/citation.cfm?doid=356810.356816

Hierarchical Blackboard (Example)

http://dl.acm.org/citation.cfm?doid=356810.356816

Hearsay-II Voice Analysis Process





Blackboard




Blackboard

KS (Knowledge Source)




Blackboard Arbiter




PARAMETER

SYLLABLE

SEGMENT



Contents

1. Introduction






7. Umwelt


9. Summary

AGENT ARCHITECTURE WITH BLACKBOARD ARCHITECTURE

Game World


Five senses

Body

Language


Knowledge Making

Decision Making

Body

Motion Making

Information Flow


Sensor

Effector

Intelligence

Agent Architecture

Agent Architecture applied Blackboard Architecture


Blackboard



Modularization has advantage of game development, because each module can be developed and improved independently. And it becomes easy to add a module in the development. More intelligent creature has more intelligent modules in its architecture.



Blackboard in Agent Architecture gives scalability and customizability.

Contents

1. Introduction






7. Umwelt


9. Summary

SUBSUMPTION ARCHITECTURE

Subsumption Architecture

INPUT OUTPUT

Time

Abstraction (verbalizing)

Reactive

More Abstract thinking

Theoretical thinking

Abstract thinking

primitive stimuli becomes language

Making a body action Making a behavior

Classical : Central domain All processes of intelligent modules are executed in sequence.

Subsumption : parallel & layered All processes of intelligent modules are executed in parallel.

Rodney Brooks, A robust layered control system for a mobile robot Robotics and Automation, IEEE Journal of (Volume:2 , Issue: 1 ) 1986

Roomba (iRobot)

http://www.irobot.com/en/us/learn/home/roomba.aspx

Roomba has a subsumption architecture.

http://www.irobot.com/en/us/learn/home/roomba.aspx


INPUT OUTPUT

Time

Reactive

R

When a robot sees an object, It turns around.


INPUT OUTPUT

Time

Reactive

R

When a robot sees an object, and Sees a cliff on the side It stops turning and gets back .


INPUT OUTPUT

Time

Reactive


Abstract thinking

R When a robot hears a sound, It stops anyway by stopping all motions.


INPUT OUTPUT

Time

Reactive



Abstract thinking

R

When a robot cleans all rooms, It goes to energy station.


INPUT OUTPUT

Time

Abstraction (verbalizing)

Reactive



Abstract thinking

primitive stimuli becomes language

Making a body action Making a behavior

Agent Architecture applied subsumption architecture.

Game World


Five senses

Body

Language


Knowledge Making

Decision Making

Body

Motion Making

Information Flow


Sensor

Effector

Intelligence

Agent Architecture

Game World


Five senses

Body

Language


Knowledge Making

Decision Making

Body

Motion Making

Memory

Sensor

Effector

Agent Architecture

Hierarchical Recognition

Synthesis of motions

Knowledge Making

Decision Making

Motion Making

Knowledge Making

Decision Making

Motion Making

Game World （Environment/Level）

Five senses

Body

Language


Knowledge Making

Decision Making

Body

Motion Making

Memory

Sensor

Effector

Agent Architecture

Hierarchical Recognition

Synthesis of motions

Knowledge Making

Decision Making

Motion Making

Knowledge Making

Decision Making

Motion Making

Distributed Layered

Architecture ＝


References

http://people.csail.mit.edu/brooks/publications.html



Contents

1. Introduction





6. Modern Agent Architecture for A game Character

7. Umwelt


9. Summary

MODERN AGENT ARCHITECTURE FOR A GAME CHARACTER

身体の反射レベル

Decision-Making

Physical Informat

ion

Abstract Informat

ion

More Abstract Informat

ion

Abstraction

Time

Decision-Making

Decision-Making

Decision-Making

Multi-Layered Blackboard

Abstraction

Abstraction

Reduction

Reduction

Reduction

World

Sensor Effector

World Dynamics

Artificial Intelligence

Decision-Making

Physical Informat

ion

Abstract Informat

ion

More Abstract Informat

ion

Abstraction

Time

Decision-Making

Decision-Making

Decision-Making

Multi-Layered Blackboard

Abstraction

Abstraction

Reduction

Reduction

Reduction

World

Sensor Effector

World Dynamics



Abstraction

Abstraction

Reduction

Reduction

Reduction

World

Object

Object image on the lowest layer (Umwelt)

Object image on the second layer

Object image on the third

layer

Object image on the top

layer

Sensor Effector



Abstraction

Abstraction

Reduction

Reduction

Reduction

World

Object




layer


layer

Sensor Effector


Information Flow

Contents

1. Introduction






7. Umwelt (Environment World)

8. Hierarchical structure / commutative diagram / Homomorphism in agent architecture

9. Summary

UMWELT

Umwelt

• “Umwelt” means a subjective world which a living thing has.

• “Umwelt” depends on its ecology.

Umwelt

Jakob Johann Baron von Uexkül, Adolf Portmann, Streifzüge durch die Umwelten von Tieren und Menschen, ROWOHLT HAMBURG,1956 http://monoskop.org/Monoskop

http://monoskop.org/Monoskop


WORLD

BODY

Umwelt

A living thing grasps an objects in the world by two hands: functional effectors and perceptual sensors.

Object

Functional Organ (Body = Effector)

Perceptual Organ (Sensor)

WORLD

BODY

Umwelt

Object



A subjective world is created by functional effectors and perceptual sensors.

WORLD

BODY

Umwelt

Object



Each living thing has its different body and sensors.

A subjective world is created by functional effectors and perceptual sensors.

WORLD

BODY

Umwelt

Object



Each living thing has a different subjective world. = Umwelt

Bee’s Umwelt Objective

World

Bee’s Umwelt

Bees are interested in flowers.




Snail's Umwelt Research

①Put a snails on a ball. ②iterate to push and pull a bar in front of the snails. ③change a frequency of the iteratetion.

Experiment

Result

In 1-3 /sec frequency, a snail did not go to the front, but Over 4 frequency, It went front.

Conclusion

A snails recognize the bar stops over 4 frequency. ＝In snails’ Umwelt, a frequency of sensors is under 4. (Human frequency is about 18.)




Snail's Umwelt Research

A child chicken is tied to a bar with rope and closed in a transparent dome which prevent sound propagation.

Experiment

Result

（Upper） Parent chicken ignored it. （Lawer） Parent chicken went to help a child.

Conclusion

In chicken’s Umwelt, voice is more important rather than visual sensor.

ユクスキュル/クリサート、「生物から見た世界」（岩波文庫）





Abstraction

Abstraction

Reduction

Reduction

Reduction

World

Object




layer


layer

Sensor Effector


Information Flow

Contents

1. Introduction






7. Umwelt (Environment World)


9. Summary

HIERARCHICAL STRUCTURE / COMMUTATIVE DIAGRAM / HOMOMORPHISM IN AGENT ARCHITECTURE


Abstraction

Abstraction

Reduction

Reduction

Reduction

World

Object




layer


layer

Sensor Effector


Information Flow

Real World

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

Image of object Image of body (=self)

R R Representation

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

Image of object Image of body (=self)

R R

R R

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

O’’ S’’

Action: f’’

Sense: p’’

R R

R R

R R

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

R

R

R

R

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

R

R

R

R

Sequence of Self

Sequence of Object

R R

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

R

R

R

R

Sequence of Self

Sequence of Object

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

R

R

R

R

Sequence of Self

Sequence of Object

“Self” is a sequence of selfs. “Object” is a sequence of objects.

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

R

R

R

R

Sequence of Self


Representation

• “Representation” is essential concept of AI.

• “Knowledge Representation” (KR) is representation of knowledge AI uses.

• To transform “real things” to KR is the most basic techniques in AI.

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

R

R

R

R

Sequence of Self


Vector to move Vector to enter

Dude, Where's My Warthog: From Pathfinding to General Spatial Competence, D. Isla, Invited talk, Artificial Intelligence and Interactive Digital Entertainment (AIIDE) 2005 http://naimadgames.com/publications.html

http://naimadgames.com/publications.html

S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

R

R

R

R


Killzone 2 Multiplayer Bots Remco Straatman, Tim Verweij, Alex Champandard | Paris Game/AI Conference 2009, Paris, June 2009 http://www.guerrilla-games.com/publications.html

http://www.guerrilla-games.com/publications.html



S (Body)

O (Object)

Action: f

O’

Sense: p

S’

Action: f’

Sense: p’

O’’ S’’

Action: f’’

Sense: p’’

R

R

R

R


Handling Complexity in the Halo 2 AI, D. Isla, GDC 2005 Dude, Where's My Warthog: From Pathfinding to General Spatial Competence, D. Isla, Invited talk, Artificial Intelligence and Interactive Digital Entertainment (AIIDE) 2005 http://naimadgames.com/publications.html

http://naimadgames.com/publications.html

Contents

1. Introduction






7. Umwelt


9. Summary

SUMMARY

Summary

• I am a game developer in game industry for more than 10 years.

• My research is focused on AI in digital game.

• There are some mathematical structures in AI.

• I want to show it in talk…

MEIS 2015 : A Multilayered Model for Artificial Intelligence of Game Character as Agent Architecture

Science

Transcript of MEIS 2015 : A Multilayered Model for Artificial Intelligence of Game Character as Agent Architecture